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Inexact joint-probabilistic chance-constrained programming with left-hand-side randomness: An application to solid waste management

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  • Sun, Wei
  • Huang, Guo H.
  • Lv, Ying
  • Li, Gongchen

Abstract

In practical waste management systems, amounts of waste transported and treated are not always equal on a daily basis. To distinguish between these two kinds of amounts and reflect their random relationships effectively, an inexact joint-probabilistic left-hand-side chance-constrained programming (IJLCP) method was developed and applied to a municipal solid waste management problem under dual uncertainties. Dual uncertainties are defined as two kinds of uncertainties existing in the same programming model. Improving upon conventional right-hand-side chance-constrained programming, the IJLCP can not only reflect uncertainties presented in terms of interval parameters (unit transportation/treatment costs, capacities of waste treatment facilities, waste generation rates, waste transportation/treatment amounts and so on) and left-hand-side random variables (the relationship between waste transportation and treatment amounts), but also examine the reliability of satisfying (or risk of violating) the entire system constraints. A non-equivalent but sufficient linearization form of IJLCP for solving this type of problem was proposed and proved in a straightforward manner. The performance of IJLCP was analyzed under scenarios at joint and individual probabilities and compared with the corresponding internal-parameter programming model. The results indicated that the net system costs would both decrease with increasing joint probability levels and decrease slightly at different individual probabilities with the same joint probabilities. The two types of dual uncertainties were discussed as well.

Suggested Citation

  • Sun, Wei & Huang, Guo H. & Lv, Ying & Li, Gongchen, 2013. "Inexact joint-probabilistic chance-constrained programming with left-hand-side randomness: An application to solid waste management," European Journal of Operational Research, Elsevier, vol. 228(1), pages 217-225.
    • Handle: RePEc:eee:ejores:v:228:y:2013:i:1:p:217-225
    DOI: 10.1016/j.ejor.2013.01.011
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    1. Qin, X.S. & Huang, G.H. & Zeng, G.M. & Chakma, A. & Huang, Y.F., 2007. "An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1331-1357, August.
    2. Y. Li & G. Huang & S. Nie, 2009. "Water Resources Management and Planning under Uncertainty: an Inexact Multistage Joint-Probabilistic Programming Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(12), pages 2515-2538, September.
    3. Dupacova, Jitka & Gaivoronski, Alexei & Kos, Zdenek & Szantai, Tamas, 1991. "Stochastic programming in water management: A case study and a comparison of solution techniques," European Journal of Operational Research, Elsevier, vol. 52(1), pages 28-44, May.
    4. X. Qin & G. Huang, 2009. "An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 661-695, March.
    5. Chang, Ni-Bin & Wang, S.F., 1997. "A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems," European Journal of Operational Research, Elsevier, vol. 99(2), pages 303-321, June.
    6. Zare M., Yahia & Daneshmand, Ahmad, 1995. "A linear approximation method for solving a special class of the chance constrained programming problem," European Journal of Operational Research, Elsevier, vol. 80(1), pages 213-225, January.
    7. Wu, X.Y. & Huang, G.H. & Liu, L. & Li, J.B., 2006. "An interval nonlinear program for the planning of waste management systems with economies-of-scale effects--A case study for the region of Hamilton, Ontario, Canada," European Journal of Operational Research, Elsevier, vol. 171(2), pages 349-372, June.
    8. Poojari, Chandra A. & Varghese, Boby, 2008. "Genetic Algorithm based technique for solving Chance Constrained Problems," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1128-1154, March.
    9. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    10. Zhang, Guoquan & Shang, Jennifer & Li, Wenli, 2011. "Collaborative production planning of supply chain under price and demand uncertainty," European Journal of Operational Research, Elsevier, vol. 215(3), pages 590-603, December.
    11. Liu, Y. & Huang, G.H. & Cai, Y.P. & Cheng, G.H. & Niu, Y.T. & An, K., 2009. "Development of an inexact optimization model for coupled coal and power management in North China," Energy Policy, Elsevier, vol. 37(11), pages 4345-4363, November.
    12. Huang, G. H., 1998. "A hybrid inexact-stochastic water management model," European Journal of Operational Research, Elsevier, vol. 107(1), pages 137-158, May.
    13. Abdelaziz, Fouad Ben, 2012. "Solution approaches for the multiobjective stochastic programming," European Journal of Operational Research, Elsevier, vol. 216(1), pages 1-16.
    Full references (including those not matched with items on IDEAS)

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    7. Pramanik, Sutapa & Jana, Dipak Kumar & Maiti, Manoranjan, 2016. "Bi-criteria solid transportation problem with substitutable and damageable items in disaster response operations on fuzzy rough environment," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 1-13.

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